Speech communications by cellular telephone are often carried out in circumstances with large noises such as inside a car or on a street. When communications are carried out in such circumstances with large noises, it is important to suppress noise signals included in speech signals. One of noise suppressing techniques is a spectral subtraction method.
A noise suppressing apparatus using the spectral subtraction method will be described below. FIG. 1 is a block diagram illustrating an example of a configuration of a conventional noise suppressing apparatus. In FIG. 1, an input speech signal including a noise signal is subjected to the windowing processing in windowing section 11 using a trapezoid window. FFT section 12 performs Fast Fourier Transform on the processed signal, and outputs thus converted speech spectrum to spectral subtraction section 14 and noise spectrum estimating section 13.
Spectral subtraction section 14 subtracts the estimated noise spectrum generated in noise spectrum estimating section 13 from the input speech spectrum. IFFT section 15 performs Inverse Fast Fourier Transform on the input spectrum to transform into a speech signal. With respect to speech signals subjected to noise suppression processing per unit time basis, overlap adding section 16 adds intervals timewise overlapping one another to superimpose, thereby obtains a timewise continuous speech signal, and outputs a speech signal with a noise suppressed.
In this way, the conventional noise suppressing apparatus cancels a noise component by subtracting an estimated noise spectrum estimated from an interval with only a noise and no speech included therein, or the like from an input speech spectrum in frequency region obtained by performing FFT on an input speech signal, and performs IFFT on the spectrum subjected to the subtraction to transform into a speech signal in time region, and thereby outputs the speech signal with a noise suppressed.
However, in the conventional noise suppressing apparatus, since the subtraction is performed with respect to the amplitude of a speech spectrum and a phase of the spectrum is not considered, estimation of noise spectrum becomes difficult in a speech signal with a low signal-to-noise ratio or a speech signal with a generated non-stationary noise, a large error is thereby generated, and therefore it is difficult to suppress noises sufficiently.